Genomic-Agent-Discovery

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full disclosure burden. It successfully indicates this is a read-only search operation and details the categories of evidence returned (therapeutic, diagnostic, prognostic). However, it omits operational details like pagination behavior, result limits, or whether the search supports wildcards/partial matches.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely efficient two-sentence structure. First sentence establishes the database and action; second sentence specifies return value categories. No redundant phrases or filler content. Information density is high with zero waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Appropriate for a simple single-parameter search tool. Given the lack of output schema, the description adequately characterizes the return value types (clinical evidence categories). For this complexity level and 100% schema coverage, no additional operational warnings or elaborations are strictly necessary, though mentioning result format would be a plus.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the parameter is already well-documented as accepting 'Gene name, disease, or variant.' The description does not add syntax details (e.g., HGVS format support) or search behavior specifics beyond what the schema provides, meeting the baseline expectation for high-coverage schemas.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly identifies the target resource (CIViC database) and expands the acronym. Specifies the three types of annotations returned (therapeutic, diagnostic, prognostic). The 'cancer-relevant' qualifier distinguishes it from general variant databases like query_clinvar or pathogenicity predictors like query_alphamissense, though it could more explicitly contrast with sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies usage context through 'cancer-relevant variants,' suggesting this is the appropriate tool for oncology-specific clinical interpretation. However, it lacks explicit guidance on when to prefer this over query_clinvar (general clinical significance) or query_pharmgkb (drug response), which are close siblings in the tool set.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.